Comparison of EEG preprocessing methods to improve the performance of the P300 speller
The classification of P300 trials in electroencephalographic (EEG) data is made difficult due the low signal-to-noise ratio (SNR) of the P300 response. To overcome the low SNR of individual trials, it is common practice to average together many consecutive trials, which effectively diminishes the random noise. Unfortunately, when more repeated trials are required for applications such as the P300 speller, the communication rate is greatly reduced. Since the noise results from background brain activity and is inherent to the EEG recording methods, signal analysis techniques like blind source ...
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Anderson, Charles; Chen, Thomas